Daniel Auclair
Impact in
- Hematology top 1%
- Multiple Myeloma Research and Treatments
- Oncology top 5%
- Peptidase Inhibition and Analysis
Papers in
- Hematology 68
- Multiple Myeloma Research and Treatments 67
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- Protein Degradation and Inhibitors 25
- Glycosylation and Glycoproteins Research 8
- Co-authors
- Lan Bo Chen (11 shared papers)Lauren Ambrogio (2 shared papers)Philippe Lagrange (1 shared paper)G. B. Mackaness (1 shared paper)Hidefumi Sasaki (8 shared papers)Louis H. Ferland (3 shared papers)Mara Rosenberg (1 shared paper)Juliann Chmielecki (1 shared paper)
- Journals
- Blood (46 papers)Cancer Research (5 papers)Agroforestry Systems (5 papers)Leukemia (4 papers)Annals of Forest Science (3 papers)
- Partner nations
- United StatesFranceCanada
In The Last Decade
Daniel Auclair
133 papers receiving 3.4k citations
Daniel Auclair's Hit Papers
Peers
Comparison fields: 5 of 155
- Hematology 817
- Oncology 807
- Oral Surgery 192
- Rheumatology 385
- Molecular Biology 1.6k
Countries citing papers authored by Daniel Auclair
This map shows the geographic impact of Daniel Auclair's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Auclair with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Auclair more than expected).
Fields of papers citing papers by Daniel Auclair
This network shows the impact of papers produced by Daniel Auclair. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Auclair. The network helps show where Daniel Auclair may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Auclair, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 137 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Whole-exome sequencing identifies a recurrent NAB2-STAT6 fusion in solitary fibrous tumors Hit paper breakdown → | 2013 | 422 |
| 2 | 2012 | 266 | |
| 3 | 1973 | 161 | |
| 4 | 2002 | 134 | |
| 5 | 2007 | 134 | |
| 6 | 1997 | 134 | |
| 7 | 2003 | 124 | |
| 8 | 2017 | 112 | |
| 9 | 2003 | 109 | |
| 10 | 2001 | 96 | |
| 11 | 2019 | 93 | |
| 12 | 1997 | 79 | |
| 13 | 1995 | 78 | |
| 14 | 2014 | 70 | |
| 15 | 2001 | 64 | |
| 16 | 2003 | 61 | |
| 17 | 2001 | 50 | |
| 18 | 2007 | 50 | |
| 19 | 2017 | 45 | |
| 20 | 2017 | 43 |
About Daniel Auclair
Daniel Auclair is a scholar working on Hematology, Molecular Biology, Cancer Research, Oncology and Plant Science, having authored 137 papers that have together received 3.5k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (67 papers), Protein Degradation and Inhibitors (25 papers), Cancer Genomics and Diagnostics (17 papers), Forest ecology and management (10 papers), Cancer Mechanisms and Therapy (9 papers), Peptidase Inhibition and Analysis (9 papers), Leaf Properties and Growth Measurement (9 papers) and Glycosylation and Glycoproteins Research (8 papers). The work is most often cited by research in Hematology (817 citations), Oncology (807 citations), Oral Surgery (192 citations), Rheumatology (385 citations) and Molecular Biology (1.6k citations). Daniel Auclair has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Lan Bo Chen, Lauren Ambrogio, Philippe Lagrange, G. B. Mackaness, Hidefumi Sasaki, Louis H. Ferland, Mara Rosenberg, Juliann Chmielecki, Michael C. Heinrich and Rachael O’Connor. Their work appears in journals such as Blood, Cancer Research, Agroforestry Systems, Leukemia and Annals of Forest Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.